CNN-Based Phase Matching for the OAM Mode Selection in Turbulence Heterodyne Coherent Mitigation Links
A novel method is proposed to select vortex beams carrying a specific orbital angular momentum (OAM) mode in turbulence heterodyne coherent mitigation (THCM) link. It is worth mentioning that intelligent phase matching (IPM) of the OAM beams based on the convolutional neural network (CNN) is the rem...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
|
| Series: | IEEE Photonics Journal |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9204363/ |
| _version_ | 1818583127005593600 |
|---|---|
| author | Chunyong Yang Kaige Shan Jun Chen Jin Hou Shaoping Chen |
| author_facet | Chunyong Yang Kaige Shan Jun Chen Jin Hou Shaoping Chen |
| author_sort | Chunyong Yang |
| collection | DOAJ |
| description | A novel method is proposed to select vortex beams carrying a specific orbital angular momentum (OAM) mode in turbulence heterodyne coherent mitigation (THCM) link. It is worth mentioning that intelligent phase matching (IPM) of the OAM beams based on the convolutional neural network (CNN) is the remarkable feature. Namely, CNN is particularly trained as the OAM modes classifier by the light intensity distribution patterns of different modes. The classifier actually acts as a mode detector to distinguish OAM modes by the map between the light intensity distribution and OAM mode, and then output mode information (MI). Specially, the phase matching technology is demonstrated to realize selection of specific OAM mode, where exploiting MI to select a specific phase mask is a characteristic of IPM. Subsequently, the phase mask is attached to the Gaussian beam to obtain the OAM beam carrying a special mode. Numerical results show a high IPM accuracy of 99% under medium strength atmospheric turbulence (AT). |
| first_indexed | 2024-12-16T08:00:20Z |
| format | Article |
| id | doaj.art-8c103b3555b1428bbb18881cc4e13792 |
| institution | Directory Open Access Journal |
| issn | 1943-0655 |
| language | English |
| last_indexed | 2024-12-16T08:00:20Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Photonics Journal |
| spelling | doaj.art-8c103b3555b1428bbb18881cc4e137922022-12-21T22:38:36ZengIEEEIEEE Photonics Journal1943-06552020-01-0112611310.1109/JPHOT.2020.30259449204363CNN-Based Phase Matching for the OAM Mode Selection in Turbulence Heterodyne Coherent Mitigation LinksChunyong Yang0https://orcid.org/0000-0002-4509-8043Kaige Shan1Jun Chen2Jin Hou3https://orcid.org/0000-0001-7055-5341Shaoping Chen4https://orcid.org/0000-0003-0027-1276Hubei Key Laboratory of Intelligent Wireless Communications, College of Electronics and Information Engineering, South-Central University for Nationalities, Wuhan, ChinaHubei Key Laboratory of Intelligent Wireless Communications, College of Electronics and Information Engineering, South-Central University for Nationalities, Wuhan, ChinaAccelink Technology Co. Ltd., Wuhan, ChinaHubei Key Laboratory of Intelligent Wireless Communications, College of Electronics and Information Engineering, South-Central University for Nationalities, Wuhan, ChinaHubei Key Laboratory of Intelligent Wireless Communications, College of Electronics and Information Engineering, South-Central University for Nationalities, Wuhan, ChinaA novel method is proposed to select vortex beams carrying a specific orbital angular momentum (OAM) mode in turbulence heterodyne coherent mitigation (THCM) link. It is worth mentioning that intelligent phase matching (IPM) of the OAM beams based on the convolutional neural network (CNN) is the remarkable feature. Namely, CNN is particularly trained as the OAM modes classifier by the light intensity distribution patterns of different modes. The classifier actually acts as a mode detector to distinguish OAM modes by the map between the light intensity distribution and OAM mode, and then output mode information (MI). Specially, the phase matching technology is demonstrated to realize selection of specific OAM mode, where exploiting MI to select a specific phase mask is a characteristic of IPM. Subsequently, the phase mask is attached to the Gaussian beam to obtain the OAM beam carrying a special mode. Numerical results show a high IPM accuracy of 99% under medium strength atmospheric turbulence (AT).https://ieeexplore.ieee.org/document/9204363/Heterodyne coherenceturbulence mitigationphase matchingorbital angular momentumconvolutional neural network |
| spellingShingle | Chunyong Yang Kaige Shan Jun Chen Jin Hou Shaoping Chen CNN-Based Phase Matching for the OAM Mode Selection in Turbulence Heterodyne Coherent Mitigation Links IEEE Photonics Journal Heterodyne coherence turbulence mitigation phase matching orbital angular momentum convolutional neural network |
| title | CNN-Based Phase Matching for the OAM Mode Selection in Turbulence Heterodyne Coherent Mitigation Links |
| title_full | CNN-Based Phase Matching for the OAM Mode Selection in Turbulence Heterodyne Coherent Mitigation Links |
| title_fullStr | CNN-Based Phase Matching for the OAM Mode Selection in Turbulence Heterodyne Coherent Mitigation Links |
| title_full_unstemmed | CNN-Based Phase Matching for the OAM Mode Selection in Turbulence Heterodyne Coherent Mitigation Links |
| title_short | CNN-Based Phase Matching for the OAM Mode Selection in Turbulence Heterodyne Coherent Mitigation Links |
| title_sort | cnn based phase matching for the oam mode selection in turbulence heterodyne coherent mitigation links |
| topic | Heterodyne coherence turbulence mitigation phase matching orbital angular momentum convolutional neural network |
| url | https://ieeexplore.ieee.org/document/9204363/ |
| work_keys_str_mv | AT chunyongyang cnnbasedphasematchingfortheoammodeselectioninturbulenceheterodynecoherentmitigationlinks AT kaigeshan cnnbasedphasematchingfortheoammodeselectioninturbulenceheterodynecoherentmitigationlinks AT junchen cnnbasedphasematchingfortheoammodeselectioninturbulenceheterodynecoherentmitigationlinks AT jinhou cnnbasedphasematchingfortheoammodeselectioninturbulenceheterodynecoherentmitigationlinks AT shaopingchen cnnbasedphasematchingfortheoammodeselectioninturbulenceheterodynecoherentmitigationlinks |